首页|Fatigue life prediction for power supporting frame off electric-driven seismic vibrator under random load
Fatigue life prediction for power supporting frame off electric-driven seismic vibrator under random load
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NSTL
Elsevier
? 2022 Elsevier LtdDeveloping electric-driven seismic vibrator is a promising way to realize green exploration. To ensure the service life of the power supporting frame under long-term operation, a method of predicting fatigue life under random load is proposed. First, stress history of the maximum stress node is obtained through dynamic analysis. Second, based on the rainflow counting method, the stress history at the maximum stress node was statistically analyzed, the distribution of amplitude and the distribution of mean are studied, and the load spectrum is compiled. Third, considering structural parameters and the stress below the fatigue limit, the P-S-N curve of the power supporting frame is achieved through two-steps corrections, and combined with the Miner's rule, the fatigue life of the power supporting frame is predicted. The results show that under the condition of the significance level of 0.05, the amplitude and the mean of the stress are independent of each other. The amplitude of stress obeys the Weibull distribution with a shape parameter of 1.0362 and a scale parameter of 10.5108, and the mean of stress obeys a normal distribution with a mean value of 40.253 and a standard deviation of 10.1803. Under 95% reliability, considering the structural parameters and the stress below the fatigue limit, a more accurate P-S-N curve of the power supporting frame is obtained, and then with Miner's rule the fatigue life of the power supporting frame is predicted to be 8.5 years. Based on this study, the power supporting frame was successfully manufactured. This research also provides method and case reference for structural fatigue life prediction under random loads.
Fatigue life predictionP-S-N curvePower supporting frameRainflow counting methodRandom load
Li G.、Qi W.、Huang Z.、Ding Y.、He L.
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School of Mechatronic Engineering Southwest Petroleum University
Department of Transportation and Municipal Engineering Sichuan College of Architectural Technology
Electronic Information Engineering Key Laboratory of Electronic Information of State Ethnic Affairs Commission College of Electrical Engineering Southwest Minzu University
NSTL
Elsevier
